Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1]
Total Stability of SVMs and Localized SVMs
Authors: Hannes Köhler, Andreas Christmann
JMLR 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | As this is a theoretical investigation, we will focus on such theoretical results, and numerical experiments will be published elsewhere. |
| Researcher Affiliation | Academia | Hannes K ohler EMAIL Andreas Christmann EMAIL Department of Mathematics University of Bayreuth 95440 Bayreuth, Germany |
| Pseudocode | No | The paper does not contain any sections explicitly labeled as "Pseudocode" or "Algorithm", nor does it present structured steps in a code-like format. It focuses on theoretical derivations and proofs. |
| Open Source Code | No | As this is a theoretical investigation, we will focus on such theoretical results, and numerical experiments will be published elsewhere. |
| Open Datasets | No | The paper is theoretical and does not conduct experiments that would involve specific datasets. While it discusses 'data sets' in a general machine learning context (e.g., 'available data set consisting of observations from P'), it does not refer to any concrete, named datasets or provide access information for data used in experiments. |
| Dataset Splits | No | The paper is a theoretical investigation and does not describe any experiments that would require dataset splits. |
| Hardware Specification | No | The paper is a theoretical investigation and does not contain any details about hardware used for experiments. |
| Software Dependencies | No | The paper is a theoretical investigation and does not provide specific software dependencies or version numbers needed to replicate any experimental results. |
| Experiment Setup | No | The paper is a theoretical investigation focusing on mathematical results and does not describe any experimental setup, hyperparameters, or training configurations. |